Remove deprecated spatial mapping and aggregation code and inputs

cases.csv

@@ -46,8 +46,8 @@ upgradescen,Exogenous upgrade capital cost specification (see inputs\upgrades).
 retscen,Retirement Scenario,Nuke60RetireYear; Nuke80RetireYear; NukeEarlyRetireYear; NukeRefRetireYear,Nuke80RetireYear,
 supplycurve,Wind and Solar Supply Curves,default; 0; naris; 2018,default,
 uraniumscen,Uranium price scenario,AEO_2025_reference; AEO_2026_baseline,AEO_2026_baseline,
-GSw_Region,Specify column from inputs/userinput/modeled_regions.csv or from {column of hierarchy.csv}/{period-delimited entries to keep from that column},N/A,country/USA,
-GSw_ZoneSet,Set of geospatial zones to use as balancing areas (described in inputs/zones/README.md),^(z48|z54|z69|z132|z134|z3109|UTcounty|PJMcounty)$,z132,
+GSw_Region,Specify {column of hierarchy.csv}/{period-delimited entries to keep from that column},N/A,country/USA,
+GSw_ZoneSet,Set of geospatial zones to use as balancing areas (described in inputs/zones/README.md),^(z48|z54|z69|z90|z132|z134|z3109|UTcounty|PJMcounty)$,z132,
 capcredit_hierarchy_level,Select level at which to aggregate net load for capacity-credit calculation,r; nercr; transreg; transgrp; cendiv; st; interconnect; country; usda_region,transreg,
 construction_schedules_suffix,File suffix for construction schedules,default,default,
 construction_times_suffix,File suffix for construction times by technology,default,default,

docs/source/faq.md

@@ -59,9 +59,9 @@ Yes, you can configure ReEDS as a single interconnect. Limiting the spatial exte
 
 The ReEDS model is capable of capturing several spatial resolutions. This aspect of the model is controlled by the `GSw_Region` and `GSw_ZoneSet` switches.
 
-- Balancing areas (BAs) and aggregated groups of BAs: Aggregation level is controlled by the 'aggreg' column of the `inputs/zones/GSw_ZoneSet/hierarchy_from134.csv` file.
+- Aggregated groups of counties: Model zone is specified by the 'r' column of the `inputs/zones/GSw_ZoneSet/hierarchy.csv` file.
   - 134 zones: `GSw_ZoneSet = z134`
-  - 132 zones (**default**): `GSw_ZoneSet = z132`. Merges p119 into p122 and p30 into p28.
+  - 132 zones (**default**): `GSw_ZoneSet = z132`. Identical to z134 except merges p119 into p122 and p30 into p28.
   - 69 zones: `GSw_ZoneSet = z69`. Obeys state, interconnect, NERC, and FERC region boundaries; most other zones below these levels are aggregated together.
   - 54 zones: `GSw_ZoneSet = z54`. Obeys state boundaries but nudges the edges of interconnect, NERC, and FERC region boundaries to align with states. Keeps CA, IL, and NY split into 2 zones and TX split into 4 zones.
   - 48 zones: `GSw_ZoneSet = z48`. Obeys state boundaries but nudges the edges of interconnect, NERC, and FERC region boundaries to align with states (highly simplified).

docs/sources.csv

@@ -685,7 +685,6 @@ RelativeFilePath,RelativeFolderPath,FileName_new,FileExtension,Description_new,I
 /inputs/userinput/ivt_default.csv,/inputs/userinput,ivt_default,.csv,,,,,,
 /inputs/userinput/ivt_small.csv,/inputs/userinput,ivt_small,.csv,,,,,,
 /inputs/userinput/ivt_step.csv,/inputs/userinput,ivt_step,.csv,ivt steps for endyears beyond 2050,,,,,
-/inputs/userinput/modeled_regions.csv,/inputs/userinput,modeled_regions,.csv,Sets of BA regions that a user can model in a run. Each column is a different region option and can be specified in cases using GSw_Region.,,,,,
 /inputs/userinput/windows_2100.csv,/inputs/userinput,windows_2100,.csv,Window size for using window solve method to 2100,,,,,
 /inputs/userinput/windows_default.csv,/inputs/userinput,windows_default,.csv,Window size for using window solve method,,,,,
 /inputs/userinput/windows_step10.csv,/inputs/userinput,windows_step10,.csv,Window size for beyond2050step10,,,,,

docs/sources_documentation.md

@@ -3434,10 +3434,6 @@
     - **Description:** ivt steps for endyears beyond 2050
 ---
 
-  - [modeled_regions.csv](/inputs/userinput/modeled_regions.csv)
-    - **Description:** Sets of BA regions that a user can model in a run. Each column is a different region option and can be specified in cases using GSw_Region.
----
-
   - [windows_2100.csv](/inputs/userinput/windows_2100.csv)
     - **Description:** Window size for using window solve method to 2100
 ---

hourlize/qaqc/summarize_supply_curves.py

@@ -83,8 +83,6 @@ def load_raw_supply_curves(rev_paths):
     args = parser.parse_args()
     rev_paths_files = args.rev_paths
     techs = args.techs
-    # only summarize ba supply curves for now
-    resolution = {'GSw_RegionResolution': 'ba'}
 
     ## set paths
     hourlize_path = os.path.dirname(os.path.realpath(__file__))
@@ -105,7 +103,7 @@ def load_raw_supply_curves(rev_paths):
             sys.exit(1)
         else:
             rev_path = pd.read_csv(rp)
-            rev_path = runreeds.get_rev_paths(rev_path, resolution)
+            rev_path = runreeds.get_rev_paths(rev_path)
             # subset to base name for sc_path
             rev_path['sc_folder'] = rev_path['sc_path'].apply(lambda row: os.path.basename(row))
             # subset to relevant columns and techs

hourlize/reeds_to_rev.py

@@ -217,22 +217,13 @@ def reaggregate_supply_curve_regions(df_sc_in, run_folder):
         ``df_sc_in`` where values of "region" are remapped to aggregated regions.
         If not, returns ``df_sc_in`` unchanged.
     """
-    sw = reeds.io.get_switches(run_folder)
-    if sw["GSw_RegionResolution"] == "county":
-        ### Map original sc regions to county
-        # pylint: disable-next=consider-using-f-string
-        df_sc_in["region"] = "p" + df_sc_in.FIPS.astype(str).map("{:>05}".format)
-
-    elif sw["GSw_RegionResolution"] == "aggreg":
-        ### Load  hierarchy file
-        hierarchy = pd.read_csv(
-            os.path.join(run_folder, "inputs_case", "hierarchy_original.csv"),
-            index_col="ba",
-        )
-        if "aggreg" in hierarchy.columns:
-            r2aggreg = hierarchy.aggreg.copy()
-            ### Map original regions to new aggreg's
-            df_sc_in["region"] = df_sc_in["region"].map(r2aggreg)
+    county2zone = reeds.io.get_county2zone(run_folder)
+    df_sc_in["region"] = (
+        df_sc_in.FIPS
+        .astype(str)
+        .map("{:>05}".format)
+        .map(county2zone)
+    )
 
     return df_sc_in
 

inputs/disaggregation/disagg_hydroexist.csv

@@ -1,4 +1,4 @@
-PCA_REG,FIPS,i,fracdata
+legacy_ba,FIPS,i,fracdata
 p1,p53007,hydUD,0.16290661070304302
 p1,p53033,hydUD,0.03384050367261281
 p1,p53057,hydUD,0.2759706190975865

inputs/userinput/futurefiles.csv

@@ -2,7 +2,6 @@ filename,filetype,ignore,key,year_col,fix_cols,wide,header,forecast_fit,clip_min
 aclike.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 acp_disallowed.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 acp_prices.csv,.csv,0,None,wide,st,1,0,constant,None,None,done,constant
-agglevels.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 allout_RSC.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 allt.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 alpha.csv,.csv,0,None,t,None,1,0,constant,None,None,done,linear_10
@@ -198,7 +197,6 @@ heat_rate_penalty_spin.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,
 heat_rate.csv,.csv,0,None,t,"i,v,r",0,0,constant,0,None,done,constant
 hierarchy_itlgrp.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hierarchy_original.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-hierarchy_with_res.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hierarchy.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 hintage_char.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hintage_data.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
@@ -256,7 +254,6 @@ min_retire_age.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 minCF.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 mingen_fixed.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 minloadfrac0.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
-modeled_regions.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 modeledyears.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 month.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 month2quarter.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
@@ -364,7 +361,6 @@ pvbcapcostmult.csv,.csv,0,None,t,None,0,0,constant,None,None,done,constant
 pvf_cap.csv,.csv,1,None,*t,None,0,0,linear_5,0,None,done (but double-check that it is written correctly by calc_financial_inputs.py),linear_5
 pvf_onm_int.csv,.csv,1,None,*t,None,0,0,linear_10,0,None,done (but double-check that it is written correctly by calc_financial_inputs.py),linear_10
 quarter.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-r_ba.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_cendiv.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_county.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_cs_distance_mi.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
@@ -479,8 +475,6 @@ upgrade_mult_mid.csv,.csv,0,None,wide,dummy,1,0,linear_5,0,None,new,
 upgradelink_water.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 uranium_price.csv,.csv,0,None,year,None,0,0,linear_5,0,None,new,
 va_ng_crf_penalty.csv,.csv,0,None,0,None,0,None,constant,None,None,done,constant
-val_ba.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-county.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 val_cs.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 val_r_all.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 var_map.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant